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@ -10,8 +10,10 @@ Installation
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Prerequisite
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------------
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The TRIQS library relies on a certain number of standard libraries described in
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the :ref:`list of requirements <requirements>`. Here are instructions to install
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The TRIQS library relies on a certain number of standard libraries and tools described in
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the :ref:`list of requirements <requirements>`. Beware in particular to the :ref:`C++ compilers<require_cxx_compilers>`
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and to :ref:`Scientific Python tools<python_install>`.
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Here are instructions to install
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these necessary libraries on two standard systems:
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.. toctree::
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@ -35,12 +37,21 @@ Installation steps
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$ cmake -DCMAKE_INSTALL_PREFIX=path_to_install_directory ../src
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If you omit CMAKE_INSTALL_PREFIX, the default `path_to_install_directory` is ./INSTALL_DIR.
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Configuration options are described :ref:`here<install_options>`.
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#. Compile the code, run the tests and install the library::
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$ make
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$ make test
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$ make install
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.. note::
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We remind you that on multicore machine, make's option -jN (where N is the number of cores)
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greatly speed up the compilation e.g. make -j8 on a 8 cores machine...
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#. After the installation TRIQS has been installed using the standard UNIX
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scheme:
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@ -53,15 +64,16 @@ Installation steps
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* shared items in ``path_to_install_directory/share/triqs``.
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Further details
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---------------
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Further reading
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------------------
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.. toctree::
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:maxdepth: 1
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installation/install_options
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installation/python
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installation/clang
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installation/intel
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installation/install_options
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installation/changelog
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..
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installation/intel
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@ -1,47 +1,44 @@
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.. index:: clang
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.. _clang:
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.. highlight:: bash
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.. _install_clang:
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Using clang compiler
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==========================
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clang++ compiler is **highly recommended** for anyone developing in C++ since :
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**clang/llvm** is one of the very best C++ compilers, with gcc.
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It is open source, on linux and OS X (where it is now the standard compiler provided by Apple).
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* It has very nice and useful error messages, much nicer than intel or gcc.
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* It implements most of the new C++11 standard.
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*clang* compiler is **highly recommended** for anyone developing in C++ since :
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clang/llvm is now the standard compiler on OS X, but it is open source
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and works very well on linux too.
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* It is standard compliant (C++11).
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* It has very nice and useful error messages, much nicer than intel or gcc (even thought gcc is catching up...).
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It really makes little sense to develop with e.g. gcc 4.6 today, specially with a library like TRIQS,
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which uses a lot of metaprogramming.
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Version
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---------
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Note however that for *production* compilations, gcc, specially recent versions, still produces in general
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a slighly more optimal code for TRIQS applications, also the difference is small.
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* TRIQS compiles on clang, version 3.0 and later.
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It is highly recommended to use the latest stable on linux (3.3), and the default compiler on Os X (Mountain lion).
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* Recommended version is 3.1 (latest stable).
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Get and install clang on linux
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---------------------------------------------
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Get and install clang
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------------------------
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Precompiled versions are available at the `LLVM dowload page <http://llvm.org/releases/download.html>`_,
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use it. Just untar them, and add the directory in your path.
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If you have precompiled version in the `LLVM dowload page <http://llvm.org/releases/download.html>`_,
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use it. E.g. on Ubuntu 12.04 LTS ::
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wget http://llvm.org/releases/3.1/clang+llvm-3.1-x86_64-linux-ubuntu_12.04.tar.gz
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tar xzf clang+llvm-3.1-x86_64-linux-ubuntu_12.04
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sudo mv clang+llvm-3.1-x86_64-linux-ubuntu_12.04 /opt/clang
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# add /opt/clang/bin to your path
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# use clang++...
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Otherwise, it is in fact quite easy to compile clang from source, just follow the
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In any case, it is also very easy to compile clang from source, just follow the
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`instructions <http://clang.llvm.org/get_started.html#build>`_.
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Usage
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--------------
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In the current version, when compiling with clang, say (provided clang++ is your path of course) ::
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To use clang ::
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CXX=clang++ cmake path_to_TRIQS_source_directory .... others options ...
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.. note::
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On Os X, the options -std=c++11 and -stdlib=libc++ are automatically added by the TRIQS installation script.
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@ -12,7 +12,7 @@ Specifying the compiler or compile/link flags
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To specify the compiler with cmake one may use the CXX, CXXFLAGS variables, e.g. ::
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CXX=clang++ CXXFLAGS cmake path_to_TRIQS_source_directory .....
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CXX=clang++ CXXFLAGS=XXXX cmake path_to_TRIQS_source_directory .....
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Customize the installation
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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@ -24,11 +24,8 @@ You can then customize the installation options using the :program:`ccmake` prog
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This opens an interface with your main installation options shown ::
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BUILD_SHARED_LIBS ON
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Build_CTHyb ON
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Build_Documentation OFF
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Build_HubbardI ON
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Build_Triqs_General_Tools_Test ON
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Build_Wien2k ON
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CMAKE_INSTALL_PREFIX /home/parcolle/BUILD2/Triqs_dynamic/INSTALL_DIR
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Install_dev OFF
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LAPACK_LIBS /usr/lib/liblapack.so;/usr/lib/libblas.so;/usr/lib/libpthread.so;/usr/lib/libblas.so
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@ -46,61 +43,4 @@ You may change all other installation options (like locations of libraries, the
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After having corrected your options you may build, test and install TRIQS as described in :ref:`installation`.
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.. _install_without_boost:
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Installation with your own version of boost [-DBOOST_INSTALL_DIR=...]
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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If you have a sufficiently recent version of boost already installed in your system you may
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link TRIQS with it instead of compiling a new version of boost from sources.
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In this case, the cmake instruction is ::
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cmake path_to_TRIQS_source_directory -DBOOST_INSTALL_DIR=root_path_to_Boost_installation ....
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The cmake option `DBOOST_INSTALL_DIR` is the path to the **boost** libraries.
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The default value is :
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* BOOST_INSTALL_DIR : /usr
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So if boost is at the right place, you can just say::
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cmake path_to_TRIQS_source_directory
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**Obviously, you should not specify `DBOOST_SOURCE_DIR` in this case!**
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.. _static_dyn :
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Static versus dynamic linking [-DBUILD_SHARED_LIBS=OFF]
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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TRIQS can be compiled in two different ways:
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* **dynamic linking** [default] :
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This is the standard python procedure and the default choice.
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All the C++ codes are compiled in shared libraries and loaded dynamically at runtime by the python interpreter.
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With this technique however, you have to properly set the PYTHONPATH environment variable to the TRIQS installation directory in order
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for python to be able to find the module. To avoid errors, TRIQS provides a
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tiny script :file:`path_to_TRIQS_install_directory/bin/pytriqs` that sets up this variable for you and launch the python interpreter.
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* **static linking** :
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An alternative is to compile a new interpreter statically.
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Here the C++ modules are linked with libpython2.x.a to create a *new python interpreter* :file:`path_to_TRIQS_install_directory/bin/pytriqs`
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that contains these modules as *built-in* modules.
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Though it is not as standard and extensible as the dynamic linking, this technique has several advantages :
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* It avoids opening dynamic libs, which simplifies code profiling for example.
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* It may be more stable on some cluster machines (the boost.mpi modules in this case is also linked statically).
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In any case, both the scripts and the way to call them remain the same in both cases::
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pytriqs myscript.py
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The choice is made with the cmake option ::
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-DBUILD_SHARED_LIBS=OFF/ON
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@ -9,8 +9,8 @@ Installing required libraries on Mac OS X
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This installation guide has been tried on Mountain Lion. It may work for older
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versions of Mac OS X but previous versions of Mac OS X are not supported.
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NB: The installation of TRIQS under previous versions of OS X requires installing clang (via Xcode) or gcc 4.7 (via MacPorts).
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On Mountain Lion, clang (llvm) replaces gcc 4.2 as the default C++ compiler.
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NB: The installation of TRIQS under previous versions of OS X requires installing clang (via Xcode).
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(On Mountain Lion, clang (llvm) replaces gcc 4.2 as the default C++ compiler).
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We strongly recommend the following installation procedure, which provides a clean way to set up all dependencies, so that all
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of them are compatible with each other. Only the installation via homebrew is supported for the Mac.
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@ -36,6 +36,9 @@ Installation of the dependencies
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brew install python
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brew install doxygen
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#AFTER THE FIX IN BOOST AND BREW : IN PROGRESS
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#brew install boost --without-single --with-mpi --with-c++11
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4. Now install virtualenv: ::
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pip install virtualenv
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@ -61,12 +64,16 @@ yield the ones located in ``$HOME/mypython``.
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pip install numpy
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pip install h5py
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pip install scipy
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pip install git+https://github.com/matplotlib/matplotlib.git#egg=matplotlib-dev
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pip install mpi4py
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pip install matplotlib
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#pip install git+https://github.com/matplotlib/matplotlib.git#egg=matplotlib-dev
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pip install tornado
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pip install pyzmq
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pip install jinja2
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pip install ipython
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pip install cython
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6. If you wish to compile the documentation locally, install sphinx, its dependencies and mathjax: ::
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pip install sphinx
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@ -60,7 +60,8 @@ Usage
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* You can install any python package for this local python installation, e.g. ::
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easy_install --upgrade ipython
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easy_install --upgrade cython
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and you have the latest ipython notebook....
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and you have the latest ipython notebook, and cython
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@ -9,10 +9,45 @@ TRIQS is built upon several python and C++ libraries, which, if not present
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already in your system, can be freely downloaded and installed. All the
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libraries and tools used by TRIQS are listed in the table:
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.. _require_cxx_compilers:
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C++ compilers
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-----------------
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TRIQS is written in C++, i.e. in the **C++11** standard as defined by the ISO.
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A recent compiler is therefore mandatory.
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There are 3 categories of C++ compilers.
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* Standard compliant C++ compilers (recommended and supported).
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* :ref:`clang 3.3<install_clang>` and higher.
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* g++ 4.8.1 and higher
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* Obsolete compilers.
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TRIQS compiles on them, but they lack full C++11 support.
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Therefore TRIQS may be slower, since some optimisations are disabled in the library
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and they may not be supported in later release.
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* g++ 4.6.4 to 4.8.0
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* C++98 compilers.
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Compilers implementing previous version of the C++ standard (c++98) do not work, and
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will *never* be supported. This includes :
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* g++ before 4.6
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* Intel icc 12.0 and below.
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Libraries
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---------------
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================== ================ ================================================================================
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Libraries/tools Version Comment
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================== ================ ================================================================================
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mpi e.g., openmpi Parallelism
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mpi openmpi Parallelism
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Since standard linux distributions (and macports on OS X)
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now provides openmpi, even on laptops, we avoid the unnecessary complication
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of maintaining a non parallel version of TRIQS
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@ -23,34 +58,11 @@ python >= 2.6.5
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scipy python mathematical library
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numpy python scientific library
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h5py python interface to hdf5 library
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mpi4py python MPI
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sphinx >= 1.0.1 python documentation tools (to compile documentation)
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pyparsing Tool for sphinx (to compile documentation)
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matplotlib >= 0.99 python 2D plotting library
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cython >=0.17 cython package
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================== ================ ================================================================================
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\* designates the libraries included in the Enthought python distribution.
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C++11
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-----
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The current version of TRIQS use the new C++11 standard, and therefore require a recent C++ compiler.
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Tested compilers include:
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* g++ 4.6.3, 4.7
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* clang++ 3.1
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* icc 13.0
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Note that older compilers will *never* be supported for current and future version of TRIQS.
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Older releases may accept older compilers.
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F90
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---
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For the Wien2TRIQS interface only.
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Tested compilers include:
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* ifort
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* gfortran
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|
@ -22,10 +22,11 @@ Install the following packages which are necessary to build TRIQS and use it::
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Optionally, you may be interested in:
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* How to *simply* upgrade the ipython notebook with :ref:`virtualenv <virtualenv>` to the latest version?
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* How to *simply* upgrade the ipython notebook and Cython with :ref:`virtualenv <virtualenv>` to the latest version?
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* How to use the nice :ref:`clang <clang>` C++ compiler?
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* How to use the nice and recommended :ref:`clang <install_clang>` C++ compiler?
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..
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* How to use :ref:`Intel <icc>` C++ compiler?
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.. warning:: you need the latest version of Cython (>=.17, downloadable on Cython.org). If Cython is not found, specify the location of the executable with the option -DCYTHON_EXECUTABLE.
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@ -3,63 +3,55 @@
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Operations : array and matrix/vector algebras
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=======================================================
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Operations
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------------
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Arithmetic operations
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-----------------------------
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Arrays and matrices can be combined in formal algebraic expressions, which models the :ref:`ImmutableCuboidArray` concept.
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This algebraic expressions can therefore be used as RHS of assignment (SEE) or in array/matrix contructors.
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For example ;
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This algebraic expressions can therefore be used in assignment array/matrix contructors.
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For example:
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.. compileblock::
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#include <triqs/arrays.hpp>
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using triqs::arrays::array;
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using triqs::arrays::array; using triqs::clef::placeholder;
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int main() {
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array<long,2> A (2,2), B(2,2), C;
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C= A + 2*B;
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array<long,2> D = A+ 2*B;
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array<double,2> F = 0.5 * A; // Type promotion is automatic
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// init
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placeholder<0> i_; placeholder<1> j_;
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array<long,2> A (2,2), B(2,2);
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A(i_,j_) << i_ + j_ ;
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B(i_,j_) << i_ - j_ ;
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// use expressions
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array<long,2> C = A+ 2*B;
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array<double,2> D = 0.5 * A; // Type promotion is automatic
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std::cout<< "A= "<< A<< std::endl;
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std::cout<< "B= "<< B<< std::endl;
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std::cout<< "C= "<< C<< std::endl;
|
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std::cout<< "D= "<< D<< std::endl;
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}
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Arrays vs matrices
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----------------------
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Because their multiplication is not the same, arrays and matrices algebras can not be mixed.
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Mixing them in expression would therefore be meaningless and it is therefore not allowed ::
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Mixing them in expression would therefore be meaningless and it is therefore not allowed.
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However, you can always use e.g. `matrix_view` from a array of rank 2 :
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array<long,2> A;
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matrix<long,2> M;
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M + A; // --> ERROR. Rejected by the compiler.
|
||||
.. compileblock::
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||||
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However, you can always make a matrix_view from a array of rank 2 ::
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||||
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||||
A + make_matrix_view(M); //--> OK.
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||||
#include <triqs/arrays.hpp>
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using namespace triqs::arrays;
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int main() {
|
||||
array<long,2> A(2,2); matrix<long,2> M(2,2);
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||||
//M + A; // --> ERROR. Rejected by the compiler.
|
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M + make_matrix_view(A); //--> OK.
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}
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||||
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||||
.. note::
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||||
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||||
Making view is cheap, it only copies the index systems. Nevertheless
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||||
this can still cause severe overhead in very intense loops.
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||||
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||||
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Compound operators (+=, -=, *=, /=)
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-------------------------------------------
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The `value classes` and the `view classes` behaves similarly.
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We will illustrate it on the `array` class, it is the same for `matrix` and `vector`.
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||||
* **Syntax**
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||||
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||||
The syntax is natural ::
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template<typename RHS> array & operator += (const RHS & X);
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template<typename RHS> array & operator -= (const RHS & X);
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template<typename RHS> array & operator *= (const Scalar & S);
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template<typename RHS> array & operator /= (const Scalar & S);
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* **Behaviour**
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- Similar to assignment, but it makes the operation
|
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- For matrices, scalar is correctly interpreted as a scalar matrix.
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||||
Making such a view is very cheap, it only copies the index systems. Nevertheless
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||||
this can still cause significant overhead in very intense loops by disturbing
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||||
optimizers.
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||||
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||||
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||||
Performance
|
||||
@ -102,6 +94,8 @@ but with several advantages :
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||||
in an optimal way, allowing machine-dependent optimization.
|
||||
* The library can perform easy optimisations behind the scene when possible, e.g. for vector it can use blas.
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||||
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||||
Expressions are lazy....
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---------------------------
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||||
Note that expressions are lazy objects. It does nothing when constructed, it just "record" the mathematical expression ::
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||||
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||||
auto e = A + 2*B; // expression, purely formal, no computation is done
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||||
@ -111,4 +105,3 @@ Note that expressions are lazy objects. It does nothing when constructed, it jus
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array<long,2> D(e); // now really makes the computation and store the result in D.
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||||
D = 2*A +B; // reassign D to the evaluation of the expression.
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||||
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||||
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||||
|
@ -44,18 +44,19 @@ ImmutableCuboidArray
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|
||||
* NB : It does not need to be stored in memory. A formal expression, e.g. model this concept.
|
||||
|
||||
* **Definition** ([A] denotes something optional).
|
||||
* **Definition** ([...] denotes something optional).
|
||||
|
||||
* The class derives from : TRIQS_CONCEPT_TAG_NAME(ImmutableCuboidArray)
|
||||
|
||||
================================================================================================== =============================================================================
|
||||
Elements Comment
|
||||
================================================================================================== =============================================================================
|
||||
domain_type Type of the domain.
|
||||
domain_type [const &] domain() const Access to the domain.
|
||||
value_type Type of the element of the array
|
||||
value_type [const &] operator() (size_t ... i) const Evaluation. Must have exactly rank argument (checked at compiled time).
|
||||
================================================================================================== =============================================================================
|
||||
+-------------------------------------------------------+-------------------------------------------------------------------------+
|
||||
| Members | Comment |
|
||||
+=======================================================+=========================================================================+
|
||||
| domain_type == cuboid_domain<Rank> | Type of the domain, with rank `Rank` |
|
||||
+-------------------------------------------------------+-------------------------------------------------------------------------+
|
||||
| domain_type [const &] domain() const | Access to the domain. |
|
||||
+-------------------------------------------------------+-------------------------------------------------------------------------+
|
||||
| value_type | Type of the element of the array |
|
||||
+-------------------------------------------------------+-------------------------------------------------------------------------+
|
||||
| value_type [const &] operator() (size_t ... i) const | Evaluation. Must have exactly rank argument (checked at compiled time). |
|
||||
+-------------------------------------------------------+-------------------------------------------------------------------------+
|
||||
|
||||
* **Examples** :
|
||||
* array, array_view, matrix, matrix_view, vector, vector_view.
|
||||
@ -69,65 +70,102 @@ MutableCuboidArray
|
||||
* **Purpose** : An array where the data can be modified...
|
||||
* **Refines** : :ref:`ImmutableCuboidArray`.
|
||||
|
||||
* **Definition**
|
||||
|
||||
* **Definition** ([A] denotes something optional).
|
||||
|
||||
* The class derives from : TRIQS_CONCEPT_TAG_NAME(MutableCuboidArray)
|
||||
|
||||
================================================================================================== =============================================================================
|
||||
Elements Comment
|
||||
================================================================================================== =============================================================================
|
||||
domain_type Type of the domain.
|
||||
domain_type [const &] domain() const Access to the domain.
|
||||
value_type Type of the element of the array
|
||||
value_type const & operator() (size_t ... i) const Element access: Must have exactly rank argument (checked at compiled time).
|
||||
value_type & operator() (size_t ... i) Element access: Must have exactly rank argument (checked at compiled time).
|
||||
================================================================================================== =============================================================================
|
||||
+----------------------------------------------+-----------------------------------------------------------------------------+
|
||||
| Members | Comment |
|
||||
+==============================================+=============================================================================+
|
||||
| value_type & operator() (size_t ... i) | Element access: Must have exactly rank argument (checked at compiled time). |
|
||||
+----------------------------------------------+-----------------------------------------------------------------------------+
|
||||
|
||||
* **Examples** :
|
||||
* array, array_view, matrix, matrix_view, vector, vector_view.
|
||||
|
||||
.. _ImmutableArray:
|
||||
|
||||
ImmutableArray
|
||||
-------------------------------------------------------------------
|
||||
|
||||
* Refines :ref:`ImmutableCuboidArray`
|
||||
|
||||
* If X is the type :
|
||||
|
||||
* ImmutableArray<A> == true_type
|
||||
|
||||
NB : this traits marks the fact that X belongs to the Array algebra.
|
||||
|
||||
.. _ImmutableMatrix:
|
||||
|
||||
ImmutableMatrix
|
||||
-------------------------------------------------------------------
|
||||
|
||||
Same as :ref:`ImmutableCuboidArray`, except that :
|
||||
* Refines :ref:`ImmutableCuboidArray`
|
||||
|
||||
* the rank of the domain must be 2
|
||||
* the class must derive from TRIQS_CONCEPT_TAG_NAME(ImmutableMatrix).
|
||||
* If A is the type :
|
||||
|
||||
* ImmutableMatrix<A> == true_type
|
||||
* A::domain_type::rank ==2
|
||||
|
||||
NB : this traits marks the fact that X belongs to the MatrixVector algebra.
|
||||
|
||||
.. _ImmutableVector:
|
||||
|
||||
ImmutableVector
|
||||
-------------------------------------------------------------------
|
||||
|
||||
Same as :ref:`ImmutableCuboidArray`, except that :
|
||||
* Refines :ref:`ImmutableCuboidArray`
|
||||
|
||||
* the rank of the domain must be 1
|
||||
* the class must derive from TRIQS_CONCEPT_TAG_NAME(ImmutableVector).
|
||||
* If A is the type :
|
||||
|
||||
* ImmutableMatrix<A> == true_type
|
||||
* A::domain_type::rank ==1
|
||||
|
||||
NB : this traits marks the fact that X belongs to the MatrixVector algebra.
|
||||
|
||||
|
||||
.. _MutableArray:
|
||||
|
||||
MutableArray
|
||||
-------------------------------------------------------------------
|
||||
|
||||
* Refines :ref:`MutableCuboidArray`
|
||||
|
||||
* If A is the type :
|
||||
|
||||
* ImmutableArray<A> == true_type
|
||||
* MutableArray<A> == true_type
|
||||
|
||||
NB : this traits marks the fact that X belongs to the Array algebra.
|
||||
|
||||
.. _MutableMatrix:
|
||||
|
||||
MutableMatrix
|
||||
-------------------------------------------------------------------
|
||||
|
||||
Same as :ref:`MutableCuboidArray`, except that :
|
||||
* Refines :ref:`MutableCuboidArray`
|
||||
|
||||
* the rank of the domain must be 2
|
||||
* the class must derive from TRIQS_CONCEPT_TAG_NAME(MutableMatrix).
|
||||
* If A is the type :
|
||||
|
||||
* ImmutableMatrix<A> == true_type
|
||||
* MutableMatrix<A> == true_type
|
||||
* A::domain_type::rank ==2
|
||||
|
||||
NB : this traits marks the fact that X belongs to the MatrixVector algebra.
|
||||
|
||||
.. _MutableVector:
|
||||
|
||||
MutableVector
|
||||
-------------------------------------------------------------------
|
||||
|
||||
Same as :ref:`MutableCuboidArray`, except that :
|
||||
* Refines :ref:`MutableCuboidArray`
|
||||
|
||||
* the rank of the domain must be 1
|
||||
* the class must derive from TRIQS_CONCEPT_TAG_NAME(MutableVector).
|
||||
* If A is the type :
|
||||
|
||||
* ImmutableMatrix<A> == true_type
|
||||
* MutableMatrix<A> == true_type
|
||||
* A::domain_type::rank ==1
|
||||
|
||||
NB : this traits marks the fact that X belongs to the MatrixVector algebra.
|
||||
|
||||
|
||||
Why concepts ? [Advanced]
|
||||
@ -153,7 +191,7 @@ Example :
|
||||
#include <iostream>
|
||||
namespace triqs { namespace arrays { // better to put it in this namespace for ADL...
|
||||
|
||||
template<typename T> class immutable_diagonal_matrix_view : TRIQS_CONCEPT_TAG_NAME(ImmutableMatrix) {
|
||||
template<typename T> class immutable_diagonal_matrix_view {
|
||||
|
||||
array_view<T,1> data; // the diagonal stored as a 1d array
|
||||
|
||||
@ -167,8 +205,12 @@ Example :
|
||||
typedef T value_type;
|
||||
T operator()(size_t i, size_t j) const { return (i==j ? data(i) : 0);} // just kronecker...
|
||||
|
||||
friend std::ostream & operator<<(std::ostream & out, immutable_diagonal_matrix_view const & d) { return out<<"diagonal_matrix "<<d.data;}
|
||||
friend std::ostream & operator<<(std::ostream & out, immutable_diagonal_matrix_view const & d)
|
||||
{return out<<"diagonal_matrix "<<d.data;}
|
||||
};
|
||||
|
||||
// Marking this class as belonging to the Matrix & Vector algebra.
|
||||
template<typename T> struct ImmutableMatrix<immutable_diagonal_matrix_view<T>> : std::true_type{};
|
||||
}}
|
||||
|
||||
/// TESTING
|
||||
|
@ -1,6 +1,6 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_reg_call:
|
||||
.. _arr_call:
|
||||
|
||||
Operator()
|
||||
==================================
|
||||
@ -15,6 +15,9 @@ Operator()
|
||||
|
||||
`clef expression` operator()( `at least a lazy argument` ) const (3)
|
||||
|
||||
This is valid for both the container (e.g. array), and the view (e.g. array_view).
|
||||
|
||||
|
||||
.. _arr_element_access:
|
||||
|
||||
(1) Element access
|
||||
|
16
doc/reference/c++/arrays/containers/compound_ops.rst
Normal file
16
doc/reference/c++/arrays/containers/compound_ops.rst
Normal file
@ -0,0 +1,16 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_comp_ops:
|
||||
|
||||
Compound assignment operators (+=, -=, * =, /=)
|
||||
-------------------------------------------------
|
||||
|
||||
**Synopsis** ::
|
||||
|
||||
template<typename RHS> THIS_TYPE & operator += (const RHS & X);
|
||||
template<typename RHS> THIS_TYPE & operator -= (const RHS & X);
|
||||
template<typename RHS> THIS_TYPE & operator *= (const Scalar & S);
|
||||
template<typename RHS> THIS_TYPE & operator /= (const Scalar & S);
|
||||
|
||||
The containers and the view have compound operators.
|
||||
|
63
doc/reference/c++/arrays/containers/memory.rst
Normal file
63
doc/reference/c++/arrays/containers/memory.rst
Normal file
@ -0,0 +1,63 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_view_memory:
|
||||
|
||||
View memory management
|
||||
------------------------
|
||||
|
||||
View classes contains a reference counting system to the memory block they view
|
||||
(like a std::shared_ptr, but more sophisticated to properly interface to Python numpy).
|
||||
|
||||
This guarantees that memory will not be dellocated before the destruction of the view.
|
||||
|
||||
The memory block will be dellocated when its array and all array_view
|
||||
pointing to it or to a portion of it will be destroyed, and only at that moment.
|
||||
|
||||
Example::
|
||||
|
||||
array<int,2> *p = new array<int,2> (2,3); // create an array p
|
||||
array_view<int,2> B = *p; // making a view
|
||||
delete p; // p is gone...
|
||||
B(0,0) = 314; cout<<B<<endl; // B (and the data) is still alive
|
||||
|
||||
|
||||
.. warning::
|
||||
|
||||
TRIQS arrays, and in particular views are NOT thread-safe, contrary to std::shared_ptr.
|
||||
This is a deliberate choice for optimisation.
|
||||
|
||||
|
||||
Weak views [Advanced]
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
|
||||
Unfortunately this can not be the end of the story, at least on current C++11 compilers.
|
||||
It turns out that, in very performance sensitive loops, increasing this tiny
|
||||
reference counter can break a lot of optimisations in almost all compilers, including the most
|
||||
recent ones (gcc 4.8, clang 3.3).
|
||||
|
||||
It was therefore decided to introduce `weak views`.
|
||||
|
||||
* Weak views are completely similar to "normal" views, except that they do `not` increase the memory
|
||||
reference counter.
|
||||
|
||||
* Normal views are be implicitely constructed from weak view (the reverse is also true),
|
||||
As soon as you store the weak view into a normal view (e.g. array_view<T,N>)
|
||||
the reference counting is again incremented, and the memory guarantee holds.
|
||||
|
||||
* Explicit construction of weak views is intentionally not documented here.
|
||||
It is designed to be (almost) an implementation detail.
|
||||
|
||||
* The () operator returns a weak view `on a fully compliant C++11 compiler` (in particular, `rvalue reference for *this` must be implemented)
|
||||
allowing therefore for better performance on such compiler, in some loops.
|
||||
Older supported compiler will therefore generate code with lower performances.
|
||||
|
||||
* It is however necessary for the advanced user to know about this implementation detail,
|
||||
because in some convolved cases, the memory guarantee may not hold.
|
||||
Example ::
|
||||
|
||||
TO BE WRITTEN
|
||||
|
||||
|
||||
|
||||
|
||||
|
18
doc/reference/c++/arrays/containers/rebind.rst
Normal file
18
doc/reference/c++/arrays/containers/rebind.rst
Normal file
@ -0,0 +1,18 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_rebind:
|
||||
|
||||
rebind
|
||||
==================================
|
||||
|
||||
* **Synopsis**:
|
||||
|
||||
.. cpp:function:: void rebind(array_view const & a)
|
||||
|
||||
Rebinds the view
|
||||
|
||||
After this method, the view points to the same as a.
|
||||
Following the :ref:`memory management rules <arr_view_memory>`, if nothing else views the
|
||||
data originally pointed to by the view, this data is destroyed.
|
||||
|
||||
|
@ -5,55 +5,40 @@
|
||||
Assignment
|
||||
=========================
|
||||
|
||||
The `value classes` and the `view classes` have a quite general assignment operator.
|
||||
|
||||
**Synopsis** ::
|
||||
|
||||
|
||||
array & operator=(array const & X); (1)
|
||||
|
||||
template<ImmutableCuboidArray RHS> array & operator=(RHS const & X); (2)
|
||||
|
||||
The container have a quite general assignment operator.
|
||||
We will illustrate it on the `array` class, it is the same for `matrix` and `vector`.
|
||||
|
||||
* **Syntax** : the syntax is the same in both cases::
|
||||
* (1) just make a copy of X.
|
||||
|
||||
template<typename RHS> array & operator=(const RHS & X);
|
||||
template<typename RHS> array_view & operator=(const RHS & X);
|
||||
|
||||
* **What can be RHS ?**
|
||||
|
||||
RHS can be ... anything that models the :ref:`ImmutableCuboidArray` concept !
|
||||
* (2) **RHS** can be anything that models the :ref:`ImmutableCuboidArray` concept
|
||||
|
||||
e.g. : array, array_view, matrix, matrix_view,
|
||||
but also formal expression (See , e.g. A+B), or any custom object of your choice.
|
||||
|
||||
* **Behaviour**
|
||||
`Effect` : all the elements viewed by the view are replaced
|
||||
by the evaluation of RHS.
|
||||
|
||||
================= ======================================================================= ======================================================================================
|
||||
Topic value class : array, matrix, vector view: array_view, matrix_view, vector_view
|
||||
================= ======================================================================= ======================================================================================
|
||||
RHS ... - RHS models the concept :ref:`ImmutableCuboidArray`. - RHS models :ref:`ImmutableCuboidArray`
|
||||
[or less ? : RHS can be evaluated in the domain_type::value_type, no domain needed.].
|
||||
Effect - array is resized to have a domain X.domain() - View's domain must match X's domain or behaviour is undefined.
|
||||
- array is filled with the evaluation of X. - array is filled with the evaluation of X.
|
||||
================= ======================================================================= ======================================================================================
|
||||
.. warning::
|
||||
|
||||
* By evaluation of X, we mean :
|
||||
In both cases, if needed, the container is resized.
|
||||
|
||||
- a copy if X is an array.
|
||||
- computing the value if X is an expression.
|
||||
|
||||
Compound operators (+=, -=, * =, /=)
|
||||
-------------------------------------------------
|
||||
|
||||
* **Syntax**
|
||||
|
||||
The syntax is natural ::
|
||||
|
||||
template<typename RHS> array & operator += (const RHS & X);
|
||||
template<typename RHS> array & operator -= (const RHS & X);
|
||||
template<typename RHS> array & operator *= (const Scalar & S);
|
||||
template<typename RHS> array & operator /= (const Scalar & S);
|
||||
|
||||
* **What can be RHS ?**
|
||||
|
||||
Same as for = operator.
|
||||
|
||||
* **Behaviour**
|
||||
|
||||
Similar to for = operator, with obvious changes.
|
||||
Hence **assignment invalidates all pointers and views to it**.
|
||||
|
||||
|
||||
Move assign operator
|
||||
---------------------------
|
||||
|
||||
**Synopsis** ::
|
||||
|
||||
array & operator=(array && X);
|
||||
|
||||
Standard move assign operator.
|
||||
Move the data of X as data of `*this`.
|
||||
|
@ -15,34 +15,34 @@ Constructors of array
|
||||
* array, matrix, vector are regular types (with value semantics).
|
||||
Hence, all these constructors make a **copy** of the data, except of course the move constructor.
|
||||
|
||||
========================================== ===========================================================================================
|
||||
Constructors of array Comments
|
||||
========================================== ===========================================================================================
|
||||
array() Empty array of size 0
|
||||
------------------------------------------ -------------------------------------------------------------------------------------------
|
||||
array(size_t, ...., size_t) From the lengths of the array dimensions, with Rank arguments (checked at compile time).
|
||||
------------------------------------------ -------------------------------------------------------------------------------------------
|
||||
array(const array &) Copy construction
|
||||
------------------------------------------ -------------------------------------------------------------------------------------------
|
||||
array(array &&) Move construction
|
||||
------------------------------------------ -------------------------------------------------------------------------------------------
|
||||
array(const T & X) Type T models the :ref:`ImmutableCuboidArray` concept.
|
||||
|
||||
- X must have the appropriate domain (checked at compile time).
|
||||
- Constructs a new array of domain X.domain() and fills it with evaluation of X.
|
||||
------------------------------------------ -------------------------------------------------------------------------------------------
|
||||
array(shape_t const &) New array with the corresponding shape (as returned by the function shape. See example
|
||||
in section XXX).
|
||||
------------------------------------------ -------------------------------------------------------------------------------------------
|
||||
array(PyObject * X) Construct a new array from the Python object X.
|
||||
|
||||
- it takes a **copy** of the data of X (or of numpy(X)) into C++.
|
||||
- X is first transformed into a numpy by the python numpy lib itself
|
||||
(as if you call numpy.array(X)) if X is not a numpy array or an array of the wrong type
|
||||
(e.g. you construct an array<double,2> from a numpy of int....), and
|
||||
copied into the array.
|
||||
.. note:: X is a borrowed reference, array does not affect its counting reference.
|
||||
========================================== ===========================================================================================
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
| Constructors of array | Comments |
|
||||
+=================================+==========================================================================================+
|
||||
| array() | Empty array of size 0 |
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
| array(size_t, ...., size_t) | From the lengths of the array dimensions, with Rank arguments (checked at compile time). |
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
| array(const array &) | Copy construction |
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
| array(array &&) | Move construction |
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
| array(const T & X) | Type T models the :ref:`ImmutableCuboidArray` concept. |
|
||||
| | - X must have the appropriate domain (checked at compile time). |
|
||||
| | - Constructs a new array of domain X.domain() and fills it with evaluation of X. |
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
| array(shape_t const &) | New array with the corresponding shape (as returned by the function shape. See example |
|
||||
| | in section XXX). |
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
| array(std::initializer_list<T>) | Initialization from a initializer_list of T. Enable for rank==1 only |
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
| explicit array(PyObject * X) | Construct a new array from the Python object X. |
|
||||
| | - it takes a **copy** of the data of X (or of numpy(X)) into C++. |
|
||||
| | - X is first transformed into a numpy by the python numpy lib itself |
|
||||
| | (as if you call numpy.array(X)) if X is not a numpy array or an array of the wrong type |
|
||||
| | (e.g. you construct an array<double,2> from a numpy of int....), and |
|
||||
| | copied into the array. |
|
||||
| | .. note:: X is a borrowed reference, array does not affect its counting reference. |
|
||||
+---------------------------------+------------------------------------------------------------------------------------------+
|
||||
|
||||
.. warning::
|
||||
The constructor from the dimensions does **NOT** initialize the array to 0
|
||||
|
@ -30,91 +30,77 @@ where triqs::ull_t is the type defined by :
|
||||
except for their algebra. Array form an array algebra, where operation are done element-wise, while matrix and vector
|
||||
form the usual algebra and vector space of linear algebra.
|
||||
|
||||
* These classes are largely interoperable, as explained below : it is easy and quick to take a
|
||||
matrix_view of an array, or vice versa.
|
||||
|
||||
Template parameters
|
||||
----------------------------
|
||||
|
||||
============================ ============================== ========================== ====================================================================
|
||||
Template parameter Accepted type Access in the class Meaning
|
||||
============================ ============================== ========================== ====================================================================
|
||||
ValueType any regular type (typically a value_type The type of the element of the array
|
||||
scalar).
|
||||
Rank int rank The rank of the array
|
||||
OptionsFlags ull_t Compile time options, see below.
|
||||
TraversalOrder ull_t Compile time options, see below.
|
||||
============================ ============================== ========================== ====================================================================
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
| Template parameter | Accepted type | Access in the class | Meaning |
|
||||
+=========================================+===============================+===============================+======================================+
|
||||
| ValueType | any regular type (typically a | value_type | The type of the element of the array |
|
||||
| | scalar). | | |
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
| Rank | int | rank | The rank of the array |
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
| :ref:`OptionsFlags<arr_templ_par_opt>` | ull_t | opt_flags | Compile time options |
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
| :ref:`TraversalOrder<arr_templ_par_to>` | ull_t | | Traversal Order for all loops |
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
|
||||
* Rank is only present for array, since matrix have rank 2 and vector rank 1.
|
||||
NB: Rank is only present for array, since matrix have rank 2 and vector rank 1.
|
||||
|
||||
* OptionFlags is a series of flags determining various options at compile time.
|
||||
The possible flags are accessible via a constexpr ull_t in triqs::arrays or a macro :
|
||||
|
||||
======================== =======================================
|
||||
Macro constexpr equivalent
|
||||
======================== =======================================
|
||||
BOUND_CHECK triqs::arrays::BoundCheck
|
||||
TRAVERSAL_ORDER_C triqs::arrays::TraversalOrderC
|
||||
TRAVERSAL_ORDER_FORTRAN triqs::arrays::TraversalOrderFortran
|
||||
DEFAULT_INIT triqs::arrays::DefaultInit
|
||||
======================== =======================================
|
||||
|
||||
|
||||
Defaults can be modified with the macros :
|
||||
|
||||
* `TRIQS_ARRAYS_ENFORCE_BOUNDCHECK` : enforce BoundCheck by default (slows down codes ! Use only for debugging purposes).
|
||||
|
||||
|
||||
* TraversalOrder is a coding of the optimal ordering of indices, given by a permutation
|
||||
evaluated at **compile time**.
|
||||
The traversal of the arrays (iterators, foreach loop) will be written and optimised for this
|
||||
order.
|
||||
|
||||
The default (0) is understood as regular C-style ordering (slowest index first).
|
||||
|
||||
Note that an array can use any index ordering in memory, and that decision is take at run time
|
||||
(this is necessary for interfacing with python numpy arrays, see below).
|
||||
The code will be correct for any order, but optimised for the TraversalOrder.
|
||||
|
||||
For a few very specials operations (e.g. regrouping of indices), the indices ordering in memory and TraversalOrder
|
||||
must coincide. This will be explicitely said below. By default, it is not necessary (but can be suboptimal).
|
||||
|
||||
The permutation P encodes the position of the index : P[0] is the fastest index, P[rank - 1] the slowest index
|
||||
(see examples below).
|
||||
|
||||
TraversalOrder is not present for vector since there is only one possibility in 1d.
|
||||
.. toctree::
|
||||
:hidden:
|
||||
|
||||
template_parameters
|
||||
|
||||
Member types
|
||||
-----------------
|
||||
--------------------------------------
|
||||
|
||||
=================== ======================================
|
||||
Member type Definitions
|
||||
=================== ======================================
|
||||
value_type ValueType
|
||||
view_type The corresponding view type
|
||||
+--------------+----------------------------------------------------------+
|
||||
| Member type | Definitions |
|
||||
+==============+==========================================================+
|
||||
| value_type | ValueType |
|
||||
+--------------+----------------------------------------------------------+
|
||||
| view_type | The corresponding view type |
|
||||
+--------------+----------------------------------------------------------+
|
||||
| regular_type | The corresponding regular type i.e. the container itself |
|
||||
+--------------+----------------------------------------------------------+
|
||||
|
||||
=================== ======================================
|
||||
Member constexpr
|
||||
--------------------------------------
|
||||
|
||||
+--------+------+-------------------------------+
|
||||
| Member | Type | Definitions |
|
||||
+========+======+===============================+
|
||||
| rank | int | Rank of the container (Rank |
|
||||
| | | for array), 2 for matrix, 1 |
|
||||
| | | for vector |
|
||||
+--------+------+-------------------------------+
|
||||
|
||||
Member functions
|
||||
---------------------
|
||||
|
||||
============================================= ==============================================
|
||||
Member function Meaning
|
||||
============================================= ==============================================
|
||||
:ref:`(constructor)<arr_reg_constr>`
|
||||
(destructor)
|
||||
:ref:`operator =<arr_reg_assign>` assigns values to the container
|
||||
:ref:`operator ()<arr_reg_call>` element of access/views/lazy expressions
|
||||
|
||||
|
||||
begin/cbegin returns iterator to the beginning
|
||||
end/cend returns iterator to the end
|
||||
:ref:`resize<arr_resize>` resize the container
|
||||
|
||||
============================================= ==============================================
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| Member function | Meaning |
|
||||
+===========================================+==========================================+
|
||||
| :ref:`(constructor)<arr_reg_constr>` | |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| (destructor) | |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| :ref:`operator =<arr_reg_assign>` | assigns values to the container |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| :ref:`operator +=,-=,*=,/=<arr_comp_ops>` | compound assignment operators |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| :ref:`operator ()<arr_call>` | element of access/views/lazy expressions |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| begin/cbegin | returns iterator to the beginning |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| end/cend | returns iterator to the end |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| :ref:`resize<arr_resize>` | resize the container |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| bool is_empty() const | Is the array empty ? |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
|
||||
|
||||
.. toctree::
|
||||
@ -122,6 +108,7 @@ end/cend returns iterator to the end
|
||||
|
||||
reg_constructors
|
||||
reg_assign
|
||||
comp_ops
|
||||
call
|
||||
resize
|
||||
STL
|
||||
@ -130,17 +117,19 @@ Non-member functions
|
||||
------------------------
|
||||
|
||||
|
||||
============================================= ==============================================
|
||||
Member function Meaning
|
||||
============================================= ==============================================
|
||||
:ref:`swap<arr_swap>`
|
||||
:ref:`deep_swap<arr_deep_swap>`
|
||||
|
||||
============================================= ==============================================
|
||||
+---------------------------------+-------------------------------------------+
|
||||
| Member function | Meaning |
|
||||
+=================================+===========================================+
|
||||
| :ref:`swap<arr_swap>` | Swap of 2 containers |
|
||||
+---------------------------------+-------------------------------------------+
|
||||
| :ref:`deep_swap<arr_deep_swap>` | Deep swap of the data of 2 containers ??? |
|
||||
+---------------------------------+-------------------------------------------+
|
||||
| :ref:`operator\<\<<arr_stream>` | Writing to stream |
|
||||
+---------------------------------+-------------------------------------------+
|
||||
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
|
||||
swap
|
||||
stream
|
||||
|
||||
|
23
doc/reference/c++/arrays/containers/stream.rst
Normal file
23
doc/reference/c++/arrays/containers/stream.rst
Normal file
@ -0,0 +1,23 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_stream:
|
||||
|
||||
operator <<
|
||||
==================================
|
||||
|
||||
**Synopsis**::
|
||||
|
||||
template <typename ValueType, int Rank, ull_t OptionsFlags=0, ull_t TraversalOrder=0>
|
||||
std::ostream & operator << (std::ostream & out, array_view<ValueType,Rank,OptionsFlags,TraversalOrder> const &);
|
||||
|
||||
template <typename ValueType, ull_t OptionsFlags=0, ull_t TraversalOrder=0>
|
||||
std::ostream & operator << (std::ostream & out, matrix_view<ValueType,OptionsFlags,TraversalOrder> const &);
|
||||
|
||||
template <typename ValueType, ull_t OptionsFlags=0>
|
||||
std::ostream & operator << (std::ostream & out, vector_view<ValueType,OptionsFlags> const &);
|
||||
|
||||
Prints the view (or the container since the view is trivially build from the container)
|
||||
to the stream out.
|
||||
|
||||
|
||||
|
51
doc/reference/c++/arrays/containers/template_parameters.rst
Normal file
51
doc/reference/c++/arrays/containers/template_parameters.rst
Normal file
@ -0,0 +1,51 @@
|
||||
Template parameters of the containers and views
|
||||
======================================================
|
||||
|
||||
.. _arr_templ_par_opt:
|
||||
|
||||
OptionFlags
|
||||
----------------------------
|
||||
|
||||
* OptionFlags is a series of flags determining various options at compile time.
|
||||
The possible flags are accessible via a constexpr ull_t in triqs::arrays or a macro :
|
||||
|
||||
======================== =======================================
|
||||
Macro constexpr equivalent
|
||||
======================== =======================================
|
||||
BOUND_CHECK triqs::arrays::BoundCheck
|
||||
TRAVERSAL_ORDER_C triqs::arrays::TraversalOrderC
|
||||
TRAVERSAL_ORDER_FORTRAN triqs::arrays::TraversalOrderFortran
|
||||
DEFAULT_INIT triqs::arrays::DefaultInit
|
||||
======================== =======================================
|
||||
|
||||
|
||||
Defaults can be modified with the macros :
|
||||
|
||||
* `TRIQS_ARRAYS_ENFORCE_BOUNDCHECK` : enforce BoundCheck by default (slows down codes ! Use only for debugging purposes).
|
||||
|
||||
.. _arr_templ_par_to:
|
||||
|
||||
TraversalOrder
|
||||
----------------------------
|
||||
|
||||
* TraversalOrder is a coding of the optimal ordering of indices, given by a permutation
|
||||
evaluated at **compile time**.
|
||||
The traversal of the arrays (iterators, foreach loop) will be written and optimised for this
|
||||
order.
|
||||
|
||||
The default (0) is understood as regular C-style ordering (slowest index first).
|
||||
|
||||
Note that an array can use any index ordering in memory, and that decision is take at run time
|
||||
(this is necessary for interfacing with python numpy arrays, see below).
|
||||
The code will be correct for any order, but optimised for the TraversalOrder.
|
||||
|
||||
For a few very specials operations (e.g. regrouping of indices), the indices ordering in memory and TraversalOrder
|
||||
must coincide. This will be explicitely said below. By default, it is not necessary (but can be suboptimal).
|
||||
|
||||
The permutation P encodes the position of the index : P[0] is the fastest index, P[rank - 1] the slowest index
|
||||
(see examples below).
|
||||
|
||||
TraversalOrder is not present for vector since there is only one possibility in 1d.
|
||||
|
||||
|
||||
|
61
doc/reference/c++/arrays/containers/view_assign.rst
Normal file
61
doc/reference/c++/arrays/containers/view_assign.rst
Normal file
@ -0,0 +1,61 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_view_assign:
|
||||
|
||||
Assignment to views
|
||||
=========================
|
||||
|
||||
**Synopsis** :
|
||||
|
||||
template<typename RHS>
|
||||
array_view & operator=(RHS const & X);
|
||||
|
||||
The `view classes` have a quite general assignment operator.
|
||||
We will illustrate it on the `array_view` class, it is the same for `matrix` and `vector`.
|
||||
|
||||
|
||||
* **RHS** can be :
|
||||
|
||||
* Anything that models the :ref:`ImmutableCuboidArray` concept
|
||||
|
||||
e.g. : array, array_view, matrix, matrix_view,
|
||||
but also formal expression (See , e.g. A+B), or any custom object of your choice.
|
||||
|
||||
`Effect` : all the elements viewed by the view are replaced
|
||||
by the evaluation of RHS.
|
||||
|
||||
.. warning::
|
||||
|
||||
The shape of the view and of RHS must match exactly or behaviour is undefined.
|
||||
|
||||
If the debug macro, :ref:`TRIQS_ARRAYS_ENFORCE_BOUNDCHECK<arr_debug_macro>` is defined,
|
||||
this condition is checked at runtime.
|
||||
|
||||
.. note::
|
||||
|
||||
We could lower this condition, since we don't need a domain here, just the evaluation
|
||||
on the indices...
|
||||
|
||||
* A scalar.
|
||||
|
||||
`Effect` : all elements viewed by the view are set to this scalar.
|
||||
|
||||
|
||||
NB : no move assign operator
|
||||
---------------------------------------
|
||||
|
||||
Note that **there is no move assign operators for views**.
|
||||
If RHS is an rvalue reference, the regular operator = is called, that
|
||||
makes a copy of the data of RHS into the elements viewed by the view.
|
||||
|
||||
This behaviour is consistent with the fact that views are *not* regular types.
|
||||
For example ::
|
||||
|
||||
array<double,2> A(3,3);
|
||||
A(range(0,2), range(0,2)) = any_function_returning_a_new_2x2_array(....);
|
||||
|
||||
In this case, the expected behaviour is that the part of A views by view at l.h.s
|
||||
is filled by the result of the function. There can not be any move semantics here.
|
||||
|
||||
As a result, std::swap algorithm does not work properly for view, hence it has
|
||||
been explicitely *deleted*. A swap function (found by ADL) is provided instead.
|
45
doc/reference/c++/arrays/containers/view_constructors.rst
Normal file
45
doc/reference/c++/arrays/containers/view_constructors.rst
Normal file
@ -0,0 +1,45 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_view_constr:
|
||||
|
||||
Constructors of views
|
||||
================================
|
||||
|
||||
Note that in practice, you rarely explicitly construct a view.
|
||||
Views are normally automatically built by the :ref:`() operator<arr_call>`.
|
||||
|
||||
Constructors of array_view
|
||||
---------------------------------------
|
||||
|
||||
Views have `view semantics`, i.e. they **never** make a copy of the data.
|
||||
|
||||
|
||||
====================================================================== =====================================================================================================
|
||||
Constructors of array_view Comments
|
||||
====================================================================== =====================================================================================================
|
||||
array_view(const array_view &) Copy construction (makes a shallow copy)
|
||||
array_view(const T & X) T is any type such that X.indexmap() and X.storage() can be used to construct a view.
|
||||
REF to concept here ....
|
||||
====================================================================== =====================================================================================================
|
||||
|
||||
|
||||
+-----------------------------------+---------------------------------------------------------------------------------------+
|
||||
| Constructors of array_view | Comments |
|
||||
+===================================+=======================================================================================+
|
||||
| array_view(const array_view &) | Copy construction: create a new view, viewing the same data. Does **not** copy data |
|
||||
+-----------------------------------+---------------------------------------------------------------------------------------+
|
||||
| array_view(const T & X) | T is any type such that X.indexmap() and X.storage() can be used to construct a view. |
|
||||
+-----------------------------------+---------------------------------------------------------------------------------------+
|
||||
| array_view(array_view &&) | Move construction (trivial here, a copy constructor is very quick anyway). |
|
||||
+-----------------------------------+---------------------------------------------------------------------------------------+
|
||||
| explicit array_view(PyObject * X) | Construct an array_view from the Python object X. Type and rank must match exactly, |
|
||||
| | or an exception if thrown |
|
||||
+-----------------------------------+---------------------------------------------------------------------------------------+
|
||||
| | .. note:: X is a borrowed reference, array does not affect its counting reference. |
|
||||
+-----------------------------------+---------------------------------------------------------------------------------------+
|
||||
|
||||
|
||||
Constructors of matrix_view, vector_view
|
||||
------------------------------------------------
|
||||
|
||||
Similar to array_view
|
@ -19,87 +19,127 @@ where triqs::ull_t is the type defined by :
|
||||
|
||||
typedef unsigned long long ull_t;
|
||||
|
||||
The view classes have the same template parameters to the regular type.
|
||||
|
||||
|
||||
* A `view` is defined as a view of a restricted portion of the array, matrix or vector.
|
||||
|
||||
* The view type of X (= array, matrix, vector) is called X_view, with the same template parameters as the regular type.
|
||||
|
||||
* A partial view models the :ref:`MutableCuboidArray`, :ref:`MutableMatrix`, :ref:`MutableVector`, like the corresponding regular type.
|
||||
* A `view` is give access to a restricted portion of the array, matrix or vector, i.e. a `partial view` of the data.
|
||||
The view can also be `complete` (i.e. show all the container).
|
||||
|
||||
* Basically X_view should be understood as a reference to the data of the viewed object,
|
||||
dressed to model the "`MutableX`" concept.
|
||||
* The views model the :ref:`MutableCuboidArray`, :ref:`MutableMatrix`, :ref:`MutableVector`, like the corresponding regular type.
|
||||
|
||||
* A view class behaves like the value class when called, put in expression, ...
|
||||
but differs from it by its behaviour under copy and assignment.
|
||||
It has a reference semantics : like a pointer or a reference, it does not make a deep copy of the data
|
||||
when copied. See :ref:`view_vs_regular` for a detailed discussion of the difference between array and array_view.
|
||||
* Views have `view semantics`, i.e. their behave like a reference to the data, they are not regular type.
|
||||
In particular, they never make copy of the data.
|
||||
See :ref:`view_vs_regular` for a detailed discussion of the difference between a regular type and its corresponding view.
|
||||
|
||||
* Views are largely interoperable : it is easy and quick to take a matrix_view of an array, or vice versa.
|
||||
Cf constructors belows.
|
||||
|
||||
* **Memory Management**
|
||||
|
||||
====================================================================== =====================================================================================================
|
||||
Constructors of array_view Comments
|
||||
====================================================================== =====================================================================================================
|
||||
array_view(const array_view &) Copy construction (makes a shallow copy)
|
||||
array_view(const T & X) T is any type such that X.indexmap() and X.storage() can be used to construct a view.
|
||||
REF to concept here ....
|
||||
====================================================================== =====================================================================================================
|
||||
Views offers a strong guarantee of the existence of the data, like a std::shared_ptr.
|
||||
Cf :ref:`arr_view_memory` for details.
|
||||
|
||||
Template parameters
|
||||
----------------------------
|
||||
|
||||
Memory management
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
| Template parameter | Accepted type | Access in the class | Meaning |
|
||||
+=========================================+===============================+===============================+======================================+
|
||||
| ValueType | any regular type (typically a | value_type | The type of the element of the array |
|
||||
| | scalar). | | |
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
| Rank | int | rank | The rank of the array |
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
| :ref:`OptionsFlags<arr_templ_par_opt>` | ull_t | opt_flags | Compile time options |
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
| :ref:`TraversalOrder<arr_templ_par_to>` | ull_t | | Traversal Order for all loops |
|
||||
+-----------------------------------------+-------------------------------+-------------------------------+--------------------------------------+
|
||||
|
||||
NB: Rank is only present for array, since matrix have rank 2 and vector rank 1.
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
|
||||
template_parameters
|
||||
|
||||
Member types
|
||||
--------------------------------------
|
||||
|
||||
+--------------+----------------------------------------------------------+
|
||||
| Member type | Definitions |
|
||||
+==============+==========================================================+
|
||||
| value_type | ValueType |
|
||||
+--------------+----------------------------------------------------------+
|
||||
| view_type | The corresponding view type, i.e. the view itself |
|
||||
+--------------+----------------------------------------------------------+
|
||||
| regular_type | The corresponding regular type |
|
||||
+--------------+----------------------------------------------------------+
|
||||
|
||||
Member constexpr
|
||||
--------------------------------------
|
||||
|
||||
+--------+------+-------------------------------+
|
||||
| Member | Type | Definitions |
|
||||
+========+======+===============================+
|
||||
| rank | int | Rank of the container (Rank |
|
||||
| | | for array), 2 for matrix, 1 |
|
||||
| | | for vector |
|
||||
+--------+------+-------------------------------+
|
||||
|
||||
Member functions
|
||||
---------------------
|
||||
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| Member function | Meaning |
|
||||
+===========================================+==========================================+
|
||||
| :ref:`(constructor)<arr_view_constr>` | |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| (destructor) | |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| :ref:`operator =<arr_view_assign>` | assigns values to the container |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| :ref:`operator +=,-=,*=,/=<arr_comp_ops>` | compound assignment operators |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| :ref:`operator ()<arr_call>` | element of access/views/lazy expressions |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| begin/cbegin | returns iterator to the beginning |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| end/cend | returns iterator to the end |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| :ref:`rebind<arr_rebind>` | rebind the view |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
| bool is_empty() const | Is the array empty ? |
|
||||
+-------------------------------------------+------------------------------------------+
|
||||
|
||||
.. note::
|
||||
|
||||
views can not be resized.
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
|
||||
view_constructors
|
||||
view_assign
|
||||
comp_ops
|
||||
call
|
||||
rebind
|
||||
STL
|
||||
|
||||
Non-member functions
|
||||
------------------------
|
||||
|
||||
View classes contains a reference counting system to the memory block they view
|
||||
(like a std::shared_ptr, but more sophisticated to properly interface to Python numpy).
|
||||
|
||||
This guarantees that memory will not be dellocated before the destruction of the view.
|
||||
|
||||
The memory block will be dellocated when its array and all array_view
|
||||
pointing to it or to a portion of it will be destroyed, and only at that moment.
|
||||
|
||||
Example::
|
||||
|
||||
array<int,2> *p = new array<int,2> (2,3); // create an array p
|
||||
array_view<int,2> B = *p; // making a view
|
||||
delete p; // p is gone...
|
||||
B(0,0) = 314; cout<<B<<endl; // B (and the data) is still alive
|
||||
|
||||
|
||||
.. warning::
|
||||
|
||||
TRIQS arrays, and in particular views are NOT thread-safe, contrary to std::shared_ptr.
|
||||
This is a deliberate choice for optimisation.
|
||||
|
||||
|
||||
Weak views [Advanced]
|
||||
^^^^^^^^^^^^^^^^^^^^^^^^
|
||||
|
||||
Unfortunately this can not be the end of the story, at least on current C++11 compilers.
|
||||
It turns out that, in very performance sensitive loops, increasing this tiny
|
||||
reference counter can break a lot of optimisations in almost all compilers, including the most
|
||||
recent ones (gcc 4.8, clang 3.3).
|
||||
|
||||
It was therefore decided to introduce `weak views`.
|
||||
|
||||
* Weak views are completely similar to "normal" views, except that they do `not` increase the memory
|
||||
reference counter.
|
||||
|
||||
* Normal views are be implicitely constructed from weak view (the reverse is also true),
|
||||
As soon as you store the weak view into a normal view (e.g. array_view<T,N>)
|
||||
the reference counting is again incremented, and the memory guarantee holds.
|
||||
|
||||
* Explicit construction of weak views is intentionally not documented here.
|
||||
It is designed to be (almost) an implementation detail.
|
||||
|
||||
* The () operator returns a weak view `on a modern C++11 compiler`,
|
||||
allowing therefore for better performance on such compiler, in some loops.
|
||||
(in particular, `rvalue reference for *this` must be implemented).
|
||||
|
||||
* It is however necessary for the advanced user to know about this implementation detail,
|
||||
because in some convolved cases, the memory guarantee may not hold.
|
||||
Example :
|
||||
|
||||
+---------------------------------+-------------------------------------------+
|
||||
| Member function | Meaning |
|
||||
+=================================+===========================================+
|
||||
| :ref:`swap<arr_swap>` | Swap of 2 containers |
|
||||
+---------------------------------+-------------------------------------------+
|
||||
| :ref:`deep_swap<arr_deep_swap>` | Deep swap of the data of 2 containers ??? |
|
||||
+---------------------------------+-------------------------------------------+
|
||||
| :ref:`operator\<\<<arr_stream>` | Writing to stream |
|
||||
+---------------------------------+-------------------------------------------+
|
||||
|
||||
|
||||
.. toctree::
|
||||
:hidden:
|
||||
|
||||
stream
|
||||
|
@ -15,10 +15,11 @@ Multidimensional arrays
|
||||
view_or_not_view
|
||||
lazy
|
||||
foreach
|
||||
simple_fnt
|
||||
map
|
||||
mapped_fnt
|
||||
algebras
|
||||
move_swap
|
||||
play_with_concept
|
||||
blas_lapack
|
||||
H5
|
||||
Interop_Python
|
||||
|
@ -8,7 +8,7 @@ Loops : the foreach constructs
|
||||
foreach and its variants are a compact and efficient way to
|
||||
perform some action of the kind
|
||||
|
||||
*For all elements of the arrays, do something*
|
||||
*For all indices of the array, do something*
|
||||
|
||||
|
||||
While this kind of construct is equivalent to write manually the *for* loops, it has
|
||||
|
@ -1,5 +1,7 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_map_fold:
|
||||
|
||||
Functional constructs : map & fold
|
||||
###########################################
|
||||
|
||||
@ -28,15 +30,13 @@ map
|
||||
|
||||
Then map(f) is a function::
|
||||
|
||||
ReturnType map(f) ( ArrayType const & A)
|
||||
template<ImmutableCuboidArray A> auto map(f) (A const &)
|
||||
|
||||
where ArrayType models the :ref:`ImmutableCuboidArray` concept
|
||||
with :
|
||||
* A::value_type == ValueType1
|
||||
* The returned type of map(f) models the :ref:`ImmutableCuboidArray` concept
|
||||
|
||||
* with value_type == ValueType1
|
||||
|
||||
and ReturnType models the :ref:`ImmutableCuboidArray` concept
|
||||
|
||||
* with the same domain as ArrayType
|
||||
* with the same domain as A
|
||||
* with value_type == ValueType2
|
||||
|
||||
* N.B. : Some cases require explicit cast, e.g. for the standard abs function (already defined in arrays/mapped_function.hpp) ,
|
||||
@ -51,7 +51,7 @@ map
|
||||
.. compileblock::
|
||||
|
||||
#include <triqs/arrays.hpp>
|
||||
using triqs::arrays::matrix; using triqs::clef::placeholder;
|
||||
using triqs::arrays::matrix; using triqs::arrays::make_matrix; using triqs::clef::placeholder;
|
||||
int main() {
|
||||
// declare and init a matrix
|
||||
placeholder<0> i_; placeholder<1> j_;
|
||||
@ -60,14 +60,10 @@ map
|
||||
// the mapped function
|
||||
auto F = triqs::arrays::map([](int i) { return i*2.5;});
|
||||
|
||||
matrix<double> B;
|
||||
B = F(A);
|
||||
std::cout<< A << B<< std::endl;
|
||||
|
||||
// works also with expressions of course
|
||||
B = F( 2*A );
|
||||
B = B + 3* F(2*A); // ok that is just an example...
|
||||
std::cout<< A << B<< std::endl;
|
||||
std::cout<< "A = " << A << std::endl;
|
||||
std::cout<< "F(A) = " << F(A) << std::endl; // oops no computation done
|
||||
std::cout<< "F(A) = " << make_matrix(F(A)) << std::endl;
|
||||
std::cout<< "3*F(2*A) = " << make_matrix(3*F(2*A)) << std::endl;
|
||||
}
|
||||
|
||||
|
||||
@ -112,12 +108,12 @@ fold
|
||||
|
||||
Many algorithms can be written in form of map/fold.
|
||||
|
||||
The function *sum* which returns the sum of all the elements of the array is implemented approximately like this
|
||||
(this function already exists in the lib, cf ???) ::
|
||||
|
||||
The function :ref:`arr_fnt_sum` which returns the sum of all the elements of the array is implemented as ::
|
||||
template <class A>
|
||||
typename A::value_type sum(A const & a) { return fold ( std::plus<typename A::value_type>()) (a); }
|
||||
|
||||
|
||||
|
||||
Note in this example :
|
||||
|
||||
* the simplicity of the code
|
||||
|
@ -1,41 +0,0 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _Mapped:
|
||||
|
||||
Simple functions on arrays
|
||||
==================================
|
||||
|
||||
The following functions are mapped on the array (using :ref:`map`):
|
||||
|
||||
`abs real imag pow cos sin tan cosh sinh tanh acos asin atan exp log sqrt floor`
|
||||
|
||||
meaning that e.g. if `A` is an array,
|
||||
real(A) models :ref:`ImmutableCuboidArray`, with the same size and returns the real part of the elements.
|
||||
In other words, it applies the function term-by-term.
|
||||
|
||||
.. note::
|
||||
|
||||
These functions do NOT compute a new array in memory, they are lazy.
|
||||
|
||||
Example :
|
||||
|
||||
.. compileblock::
|
||||
|
||||
#include <triqs/arrays.hpp>
|
||||
using triqs::arrays::matrix; using triqs::clef::placeholder;
|
||||
|
||||
int main(){
|
||||
placeholder<0> i_; placeholder<1> j_;
|
||||
matrix<double> A(2,2);
|
||||
A(i_,j_) << i_ - j_ ;
|
||||
|
||||
std::cout << "A = "<<A << std::endl;
|
||||
std::cout << "abs(A)= "<<matrix<double>(abs(A))<< std::endl;
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
59
doc/reference/c++/arrays/play_with_concept.rst
Normal file
59
doc/reference/c++/arrays/play_with_concept.rst
Normal file
@ -0,0 +1,59 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_play_concept:
|
||||
|
||||
.. warning::
|
||||
|
||||
This part is alpha : work in progress. May change at any time.
|
||||
|
||||
Using basic concepts
|
||||
###########################################
|
||||
|
||||
|
||||
make_immutable_array
|
||||
-------------------------------
|
||||
|
||||
**Synopsis**::
|
||||
|
||||
template<typename Expr, int ... ph> auto make_immutable_array(Expr const &, clef::pair<ph,range> ...); (1)
|
||||
template<typename Function> auto make_immutable_array(Function, range ...); (2)
|
||||
|
||||
* (1)
|
||||
From a clef expression, and a range for each placeholder in the expression, build
|
||||
a lazy object modelling :ref:`ImmutableCuboidArray` concept, with the domain built from the ranges :
|
||||
|
||||
Parameters are :
|
||||
|
||||
* expr The lazy expression
|
||||
* i_=R : `i_` is a placeholder, R a range. The `i_=R` produce a clef::pair of `i_` and R , which is the parameter.
|
||||
|
||||
* (2)
|
||||
From a function object and a set of range, build
|
||||
a lazy object modelling :ref:`ImmutableCuboidArray` concept, with the domain built from the ranges :
|
||||
|
||||
|
||||
**Example** :
|
||||
|
||||
.. compileblock::
|
||||
|
||||
#include <triqs/arrays.hpp>
|
||||
#include <triqs/arrays/make_immutable_array.hpp>
|
||||
using triqs::arrays::array; using triqs::arrays::range; using triqs::clef::placeholder;
|
||||
int main() {
|
||||
placeholder<0> i_; placeholder<1> j_;
|
||||
|
||||
auto a = make_immutable_array( 1.0/(2 + i_ + j_), i_= range(0,2), j_=range(0,2));
|
||||
|
||||
std::cout << "a = " << a << std::endl;
|
||||
std::cout << "a = " << array<double,2>(a) << std::endl;
|
||||
|
||||
// or if you prefer using a lambda...
|
||||
auto b = make_immutable_array ( [](int i, int j) { return i-j;}, range (0,2), range(0,2));
|
||||
|
||||
std::cout << "b = " << b << std::endl;
|
||||
std::cout << "b = " << array<double,2>(b) << std::endl;
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
70
doc/reference/c++/arrays/simple_fnt.rst
Normal file
70
doc/reference/c++/arrays/simple_fnt.rst
Normal file
@ -0,0 +1,70 @@
|
||||
.. highlight:: c
|
||||
|
||||
.. _arr_simple_fun:
|
||||
|
||||
Simple array functions
|
||||
==================================
|
||||
|
||||
The following functions work for any object modeling :ref:`ImmutableCuboidArray` concept.
|
||||
|
||||
In this section, we present some simple functions already in the library.
|
||||
It is however very easy to create new one using the usual functional constructions :ref:`map and fold<arr_map_fold>`.
|
||||
|
||||
|
||||
Element-wise functions
|
||||
---------------------------
|
||||
|
||||
The following functions are mapped on the array (using :ref:`map`):
|
||||
|
||||
`abs real imag pow cos sin tan cosh sinh tanh acos asin atan exp log sqrt floor`
|
||||
|
||||
meaning that e.g. if `A` is an array,
|
||||
real(A) models :ref:`ImmutableCuboidArray`, with the same size and returns the real part of the elements.
|
||||
In other words, it applies the function term-by-term.
|
||||
|
||||
.. note::
|
||||
|
||||
These functions do NOT compute a new array in memory, they are lazy.
|
||||
|
||||
|
||||
sum
|
||||
---------------
|
||||
|
||||
**Synopsis**::
|
||||
|
||||
template<ImmutableCuboidArray A> A::value_type sum (A const &);
|
||||
template<ImmutableCuboidArray A> A::value_type prod (A const &);
|
||||
|
||||
Returns the sum (resp. product) of the all the elements of the array.
|
||||
|
||||
max_element, min_element
|
||||
-------------------------------
|
||||
|
||||
**Synopsis**::
|
||||
|
||||
template<ImmutableCuboidArray A> A::value_type max_element (A const &);
|
||||
template<ImmutableCuboidArray A> A::value_type min_element (A const &);
|
||||
|
||||
Returns the maximum/minimum element of the array (provided that value_type is an ordered type of course...).
|
||||
|
||||
|
||||
Examples
|
||||
-----------------
|
||||
|
||||
.. compileblock::
|
||||
|
||||
#include <triqs/arrays.hpp>
|
||||
#include <triqs/arrays/algorithms.hpp>
|
||||
using triqs::arrays::matrix; using triqs::clef::placeholder;
|
||||
int main() {
|
||||
// declare and init a matrix
|
||||
placeholder<0> i_; placeholder<1> j_;
|
||||
matrix<int> A (2,2); A(i_,j_) << i_ - j_ ;
|
||||
|
||||
std::cout << "A = " << A << std::endl;
|
||||
std::cout << "abs(A)= " << matrix<double>(abs(A)) << std::endl;
|
||||
std::cout << "sum(A) = " << sum(A) << std::endl;
|
||||
std::cout << "max_element(A) = " << max_element(A) << std::endl;
|
||||
std::cout << "min_element(A) = " << min_element(A) << std::endl;
|
||||
std::cout << "min_element(abs(A)) = " << min_element(abs(A)) << std::endl;
|
||||
}
|
@ -12,6 +12,5 @@ C++ libraries
|
||||
mctools/intro
|
||||
det_manip/det_manip
|
||||
parameters/parameters
|
||||
lectures/contents
|
||||
utilities/contents
|
||||
|
||||
|
@ -71,7 +71,7 @@ An alternative declaration with an explicit construction of the underlying mesh:
|
||||
double beta=10;
|
||||
int Nfreq =100;
|
||||
|
||||
auto GF = make_gf<imfreq>(mesh<imfreq>{beta,Fermion,Nfreq}, make_shape(1,1), local::tail(1,1));
|
||||
auto GF = make_gf<imfreq>(gf_mesh<imfreq>{beta,Fermion,Nfreq}, make_shape(1,1), local::tail(1,1));
|
||||
// or even simpler
|
||||
auto GF2 = make_gf<imfreq>({beta,Fermion,Nfreq}, make_shape(1,1), local::tail(1,1));
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user